Regional NOx emission inversion through a four-dimensional variational approach using SCIAMACHY tropospheric NO2 column observations

In this paper, the NOx emission scaling factors applied over the 2001 National Emissions Inventory (NEI) are estimated through a four-dimensional variational (4D-Var) approach using SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY) tropospheric NO₂ columns measured during summer 2004. In the “top-down” approach, two-month average NO₂ columns are assimilated into a regional chemical transport model (CTM), STEM, using different assimilation setups. In a basic setup, NOx emissions are adjusted by assimilating the NO₂ columns. A more general setup of emission inversion allows the initial O₃ concentrations be adjusted along with the NOx emissions. A final case is set up to assimilate both the NO₂ columns and O₃ measurement from various platforms while allowing adjustments of both the NOx emissions and the initial O₃ concentrations. It is found that the addition of O₃ measurements did not improve the NOx emission inversion. With the NOx emission at surface and upper levels being adjusted separately, results from four cases show that the elevated NOx emission reduction ranges from 8.9% to 11.4%, and the surface NOx emission reduction is up to 6.6%. All the cases show NOx emission reduction in Ohio valley and Washington, District of Columbia areas.     

Comparison of the MOVES2010a,MOBILE6.2, and EMFAC2007 mobile source emission models with on-road traffic tunnel and remote sensing measurements

The Desert Research Institute conducted an on-road mobile source emission study at a traffic tunnel in Van Nuys, California, in August 2010 to measure fleet-averaged, fuel-based emission factors. The study also included remote sensing device (RSD) measurements by the University of Denver of 13,000 vehicles near the tunnel. The tunnel and RSD fleet-averaged emission factors were compared in blind fashion with the corresponding modeled factors calculated by ENVIRON International Corporation using U.S. Environmental Protection Agency's (EPA's) MOVES2010a (Motor Vehicle Emissions Simulator) and MOBILE6.2 mobile source emission models, and California Air Resources Board's (CARB's) EMFAC2007 (EMission FACtors) emission model. With some exceptions, the fleet-averaged tunnel, RSD, and modeled carbon monoxide (CO) and oxide of nitrogen (NO_x) emission factors were in reasonable agreement (±25%). The nonmethane hydrocarbon (NMHC) emission factors (specifically the running evaporative emissions) predicted by MOVES were insensitive to ambient temperature as compared with the tunnel measurements and the MOBILE- and EMFAC-predicted emission factors, resulting in underestimation of the measured NMHC/NO_x ratios at higher ambient temperatures. Although predicted NMHC/NO_x ratios are in good agreement with the measured ratios during cooler sampling periods, the measured NMHC/NO_x ratios are 3.1, 1.7, and 1.4 times higher than those predicted by the MOVES, MOBILE, and EMFAC models, respectively, during high-temperature periods. Although the MOVES NO_x emission factors were generally higher than the measured factors, most differences were not significant considering the variations in the modeled factors using alternative vehicle operating cycles to represent the driving conditions in the tunnel. The three models predicted large differences in NO_x and particle emissions and in the relative contributions of diesel and gasoline vehicles to total NO_x and particulate carbon (TC) emissions in the tunnel.

Implications: Although advances have been made to mobile source emission models over the past two decades, the evidence that mobile source emissions of carbon monoxide and hydrocarbons in urban areas were underestimated by as much as a factor of 2–3 in past inventories underscores the need for on-going verification of emission inventories. Results suggest that there is an overall increase in motor vehicle NMHC emissions on hot days that is not fully accounted for by the emission models. Hot temperatures and concomitant higher ratios of NMHC emissions relative to NO_x both contribute to more rapid and efficient formation of ozone. Also, the ability of EPA's MOVES model to simulate varying vehicle operating modes places increased importance on the choice of operating modes to evaluate project-level emissions.     

Real-world fuel use and gaseous emission rates for flex fuel vehicles operated on E85 versus gasoline

Flex fuel vehicles (FFVs) typically operate on gasoline or E85, an 85%/15% volume blend of ethanol and gasoline. Differences in FFV fuel use and tailpipe emission rates are quantified for E85 versus gasoline based on real-world measurements of five FFVs with a portable emissions measurement system (PEMS), supplemented chassis dynamometer data, and estimates from the Motor Vehicle Emission Simulator (MOVES) model. Because of inter-vehicle variability, an individual FFV may have higher nitrogen oxide (NO_x) or carbon monoxide (CO) emission rates on E85 versus gasoline, even though average rates are lower. Based on PEMS data, the comparison of tailpipe emission rates for E85 versus gasoline is sensitive to vehicle-specific power (VSP). For example, although CO emission rates are lower for all VSP modes, they are proportionally lowest at higher VSP. Driving cycles with high power demand are more advantageous with respect to CO emissions, but less advantageous for NO_x. Chassis dynamometer data are available for 121 FFVs at 50,000 useful life miles. Based on the dynamometer data, the average difference in tailpipe emissions for E85 versus gasoline is ?23% for NO_x, ?30% for CO, and no significant difference for hydrocarbons (HC). To account for both the fuel cycle and tailpipe emissions from the vehicle, a life cycle inventory was conducted. Although tailpipe NO_x emissions are lower for E85 versus gasoline for FFVs and thus benefit areas where the vehicles operate, the life cycle NO_x emissions are higher because the NO_x emissions generated during fuel production are higher. The fuel production emissions take place typically in rural areas. Although there are not significant differences in the total HC emissions, there are differences in HC speciation. The net effect of lower tailpipe NO_x emissions and differences in HC speciation on ozone formation should be further evaluated.

Implications: Reported comparisons of flex fuel vehicle (FFV) tailpipe emission rates for E85 versus gasoline have been inconsistent. To date, this is the most comprehensive evaluation of available and new data. The large range of inter-vehicle variability illustrates why prior studies based on small sample sizes led to apparently contradictory findings. E85 leads to significant reductions in tailpipe nitrogen oxide (NO_x) and carbon monoxide (CO) emission rates compared with gasoline, indicating a potential benefit for ozone air quality management in NO_x-limited areas. The comparison of FFV tailpipe emissions between E85 and gasoline is sensitive to power demand and driving cycles.     

Deriving fuel-based emission factor thresholds to interpret heavy-duty vehicle roadside plume measurements

Remote sensing devices have been used for decades to measure gaseous emissions from individual vehicles at the roadside. Systems have also been developed that entrain diluted exhaust and can also measure particulate matter (PM) emissions. In 2015, the California Air Resources Board (CARB) reported that 8% of in-field diesel particulate filters (DPF) on heavy-duty (HD) vehicles were malfunctioning and emitted about 70% of total diesel PM emissions from the DPF-equipped fleet. A new high-emitter problem in the heavy-duty vehicle fleet had emerged. Roadside exhaust plume measurements reflect a snapshot of real-world operation, typically lasting several seconds. In order to relate roadside plume measurements to laboratory emission tests, we analyzed carbon dioxide (CO₂), oxides of nitrogen (NO_X), and PM emissions collected from four HD vehicles during several driving cycles on a chassis dynamometer. We examined the fuel-based emission factors corresponding to possible exceedances of emission standards as a function of vehicle power. Our analysis suggests that a typical HD vehicle will exceed the model year (MY) 2010 emission standards (of 0.2 g NO_X/bhp-hr and 0.01 g PM/bhp-hr) by three times when fuel-based emission factors are 9.3 g NO_X/kg fuel and 0.11 g PM/kg using the roadside plume measurement approach. Reported limits correspond to 99% confidence levels, which were calculated using the detection uncertainty of emissions analyzers, accuracy of vehicle power calculations, and actual emissions variability of fixed operational parameters. The PM threshold was determined for acceleration events between 0.47 and 1.4 mph/sec only, and the NO_X threshold was derived from measurements where after-treatment temperature was above 200°C. Anticipating a growing interest in real-world driving emissions, widespread implementation of roadside exhaust plume measurements as a compliment to in-use vehicle programs may benefit from expanding this analysis to a larger sample of in-use HD vehicles.

Implications: Regulatory agencies, civil society, and the public at large have a growing interest in vehicle emission compliance in the real world. Leveraging roadside plume measurements to identify vehicles with malfunctioning emission control systems is emerging as a viable new and useful method to assess in-use performance. This work proposes fuel-based emission factor thresholds for PM and NOx that signify exceedances of emission standards on a work-specific basis by analyzing real-time emissions in the laboratory. These thresholds could be used to prescreen vehicles before roadside enforcement inspection or other inquiry, enhance and further develop emission inventories, and potentially develop new requirements for heavy-duty inspection and maintenance (I/M) programs, including but not limited to identifying vehicles for further testing.     

Modelling the atmospheric transport and deposition of sulphur and nitrogen over the United Kingdom and assessment of the influence of SO2 emissions from international shipping

A statistical Lagrangian atmospheric transport model was used to generate annual maps of deposition of sulphur and oxidised and reduced nitrogen for the UK at a 5×5 km² resolution. The model was run using emissions for the year 2002. The model was compared with measurements of gas concentrations (SO₂, NO_x, HNO₃ and NH₃) and of wet deposition and aerosol concentrations of SO₄²⁻, NO₃⁻ and NH₄⁺ from national monitoring networks. Good correlation was obtained, demonstrating that the model is capable of accurately estimating the mass balance and spatial distribution of sulphur and nitrogen compounds in the atmosphere. A future emissions scenario for the year 2020 was used to test the influence of shipping emissions on sulphur deposition in the UK. The results show that, if shipping emissions are assumed to increase at a rate of 2.5% per year, their relative contribution to sulphur deposition is expected to increase from 9% to 28% between 2002 and 2020. The model was compared to both a European scale and a global scale chemical transport model and found to give broad agreement with the magnitude and location of sulphur deposition associated with shipping emissions. Enforcement of the MARPOL convention to reduce the sulphur content in marine fuel to 1% was estimated to result in a 6% reduction in total sulphur deposition to the UK for the year 2020. The percentage area of sensitive habitats with exceedance of critical loads for acidity in the UK was predicted to decrease by 1% with the implementation of the MARPOL convention.     

On-Road,In-Use Gaseous Emission Measurements by Remote Sensing of School Buses Equipped with Diesel Oxidation Catalysts and Diesel Particulate Filters

Abstract

A remote sensing device was used to obtain on-road and in-use gaseous emission measurements from three fleets of schools buses at two locations in Washington State. This paper reports each fleet’s carbon monoxide (CO), hydrocarbon (HC), nitric oxide (NO), and nitrogen dioxide (NO₂) mean data. The fleets represent current emission retrofit technologies, such as diesel particulate filters and diesel oxidation catalysts, and a control fleet. This study shows that CO and HC emissions decrease with the use of either retrofit technology when compared with control buses of the same initial emission standards. The CO and HC emission reductions are consistent with published U.S. Environmental Protection Agency verified values. The total oxides of nitrogen (NO_x), NO, and the NO₂/NO_x ratio all increase with each retrofit technology when compared with control buses. As was expected, the diesel particulate filters emitted significantly higher levels of NO₂ than the control fleet because of the intentional conversion of NO to NO₂ by these systems. Most prior research suggests that NO_x emissions are unaffected by the retrofits; however, these previous studies have not included measurements from retrofit devices on-road and after nearly 5 yr of use. Two 2006 model-year buses were also measured. These vehicles did not have retrofit devices but were built to more stringent new engine standards. Reductions in HCs and NO_x were observed for these 2006 vehicles in comparison to other non-retrofit earlier model-year vehicles.     

Evaluation of the reactive and optics model of emissions (ROME)

The reactive and optics model of emissions (ROME) is a reactive plume visibility model that simulates the potential atmospheric impacts of stack emissions. We present here an evaluation of the ability of ROME to simulate several plume physical and chemical variables, using an experimental data base that consists of a total of 40 case studies from four field programs. The evaluation variables include plume height, horizontal width, NO_x and SO₂ maximum concentrations, NO₂/NO_x concentration ratio at the plume centerline, and plume-to-sky radiance ratios. Three algorithms used to simulate plume dispersion in ROME were compared: (1) the empirical Pasquill–Gifford–Turner (PGT) scheme, (2) a first-order closure (FOC) algorithm and (3) a second-order closure (SOC) algorithm that simulates the instantaneous plume dimensions.The plume height results show a correlation of 0.82 between simulated and measured values and a gross error that is 13% of the mean measured value. For plume horizontal dispersion, the second-order closure algorithm produces a moderate correlation (0.54) and a small bias (5% of the mean measured value) in comparison with the field data. Although the PGT scheme also demonstrates moderate correlation with the measurements, it produces a negative bias by significantly underestimating plume horizontal dispersion. The first-order closure algorithm overestimates plume width and shows the least correlation (with the measurements) of the three dispersion algorithms.For the NYSEG data set where coordinated measurements of stack emissions, meteorology at plume height and plume characteristics were available, the SOC algorithm provides better correlations for NO_x concentrations, NO₂/NO_x ratios and plume visibility than the FOC and PGT algorithms. For plume visibility, the SOC algorithm shows a correlation of 0.96 at 405 nm, the wavelength where the plume was visible, and it simulates no visible plume at the other wavelengths (550 and 700 nm).A comparison of ROME simulations with those of the plume visibility model PLUVUE II shows that ROME, with the SOC algorithm, performs better for all variables.     

Modelling and assessing trends in traffic-related emissions using a generalised additive modelling approach

A generalised additive modelling (GAM) approach is used to model daily concentrations of nitrogen oxides (NO_X), nitrogen dioxide (NO₂), carbon monoxide (CO), benzene and 1,3-butadiene at a busy street canyon location in central London. The models were developed for the period July 1998–June 2005 using appropriate meteorological and road traffic covariates. For all models, the complex and localised wind-flow patterns resulting from the street canyon location of the monitoring site, which can be difficult to model deterministically, have a large influence on the model predictions. It is shown that GAMs built using simple covariates explain a large amount of the daily variation for these pollutants (mean r²=0.86). It is found that concentrations of benzene and 1,3-butadiene have declined in line with detailed calculations of emissions trends, with some evidence to suggest that reductions in benzene have been greater than estimated reductions in emissions. Although measured concentrations of NO_X have declined from 1998 to 2005, much of the decline appears to be associated with reductions in overall traffic and meteorological factors rather than reduced emissions of NO_X. Unadjusted NO_X trends show a 28.6% reduction (95% confidence interval from 21.2% to 35.8%) from 1998 to 2005, whereas meteorologically adjusted trends show a 19.3% decline (95% confidence interval from 14.8% to 23.5%) over this period. Analysis shows that there were a higher number of occasions in the early part of the time series that led to strong recirculation of exhaust emissions and higher NO_X concentrations at this location, thus affecting observed trends in concentration.     

Sensitivity of ozone to precursor emissions in urban Beijing with a Monte Carlo scheme

In order to understand the formation mechanisms of high surface ozone and identify the main contributor sources in Beijing, this study investigates the sensitivity of surface ozone to NO, NO₂ and nine types of NMVOC emissions during a photochemical smog episode. Monte Carlo sensitivity analysis scheme with fifty simulations is established based on the Nested Air Quality Prediction Model System (NAQPMS). At every simulation, each of the eleven precursor emissions is perturbed with a distinct set of perturbations. The sensitivities of ozone to emissions are identified by multiple linear regressions. The stability of sensitivity results is validated by two experiments with standard deviations of log-normal perturbations set as 30% and 50% respectively. The sensitivity results suggest that the current high surface ozone is strongly stimulated by NMVOC emissions. Among NMVOC emissions, formaldehyde, ethylene and olefins emissions present the greatest impacts on ozone. On the other hand, NOx emissions have a strong inhibitory effect on ozone formation, even after 50% NOx emission reduction. This indicates that the current ozone formation in Beijing is under NOx-saturated conditions. A transition of ozone formation is observed from NOx-saturated to NOx-limited sensitivity behavior with a 75% reduction of NOx emissions. This study gives the implication that abatement of the four NMVOC types mentioned above could be efficient on reducing the high levels of surface ozone in central urban Beijing, while inadequate abatement in NOx emissions probably induces reverse effects.     

Identification and assessment of ship emissions and their effects in the harbour of Göteborg,Sweden

The effect of ship emissions in the urban environment of Göteborg has been studied by multivariate analysis. The simultaneous measurements of relevant gases and sub-micron particles make identification of ship plumes possible. Increased concentrations of these species due to ship emissions are quantified for ships entering the inner part of the harbour. Annual depositions of SO₂ and NO₂ are estimated to be 220 and 115 kg km⁻² yr⁻¹, respectively. Exposure of transient particles (less than 0.1 μm in diameter) to this part of the harbour increased by a factor of 3 in number concentration when a ship plume was recorded. Ni, Pb, V and Zn are shown to have positive correlation with NO emissions from ships.     

Analysis and modelling of the pollutant emissions from European cars regarding the driving characteristics and test cycles

Within the European research project ARTEMIS, significant works have been conducted to analyse the hot emissions of pollutant from the passenger cars regarding the driving cycles and to propose modelling approaches taking into account large but heterogeneous datasets recorded in Europe. The review and analysis of a large range of test cycles enabled first the building-up of a set of contrasted cycles specifically designed for characterizing the influence of the driving conditions. These cycles were used for the measurement of the pollutants emission rates from nine passenger cars on a chassis dynamometer.Emissions measured on 30 vehicles tested on cycles adapted to their motorization (i.e., cycles for high- or low-powered cars, inducing thus a significant difference in the dynamic) were also considered for analysing the influence of the cycles and of the kinematic parameters on the hot emission rates of the regulated pollutants (CO, HC, NO_x, CO₂, PM). An analyses of variance demonstrated the preponderance of the driving type (urban, rural road, motorway), of the vehicle category (fuel, emission standard) and emitting status (high/normal emitter) and thus the pertinence of analysing and modelling separately the corresponding emissions. It also demonstrated that Urban driving led systematically to high diesel emission rates and to high CO₂, HC and NO_x emissions from petrol cars. Congested driving implied high CO₂ (diesel and petrol) and high diesel NO_x emission. On motorway, the very high speeds generated high CO₂, while unsteady speeds induced diesel NO_x and petrol CO over-emissions. A search for pertinent kinematic parameters showed that urban diesel emissions were mostly sensitive to stops and speed parameters, while petrol emissions were rather sensitive to acceleration parameters. On the motorway, diesel NO_x and CO₂ emissions rates increased with the speed variability and occurrence of high speeds, while CO₂ and CO over-emission from petrol cars were linked to the occurrence of strong acceleration at high speeds.A modelling approach based on partial least square regression was tested, which demonstrates its ability to discriminate satisfactorily the emissions according to dynamic related parameters and in particular when considering the two-dimensionnal distribution of instantaneous speed and acceleration.Finally, a strategy was proposed to analyse the large but heterogeneous set of hot emission data collected within the ARTEMIS project. The approach consisted in analysing the similarity of the numerous cycles as regards their kinematic, grouping them into reference test patterns through an automatic clustering, and then computing reference emissions for these patterns. These principles enabled the development of a method to compute the emissions at a low spatial scale, i.e. the so-called traffic situation approach, which was implemented in the European Artemis model for estimating the cars’ pollutant emissions.     

On-road comparison of a portable emission measurement system with a mobile reference laboratory for a heavy-duty diesel vehicle

On-road comparisons were made between a mobile emissions laboratory (MEL) meeting federal standards and a portable emissions measurement system (PEMS). These comparisons were made over different conditions; including road grade, vibration, altitude, electric fields, and humidity with the PEMS mounted inside and outside of the tractor's cab. Brake-specific emissions were calculated to explore error differences between the MEL and PEMS during the Not-To-Exceed (NTE) engine operating zone. The PEMS brake-specific NOx (bsNOx) NTE emissions were biased high relative to the MEL and, in general, were about 8% of the 2007 in-use NTE NO_x standard of 2.68 g kW^?1 h^?1 (2.0 g hp^?1 h^?1). The bsCO₂ emissions for the PEMS were also consistently biased high relative to the MEL, with an average deviation of +4% ± 2%. NMHC and CO emissions were very low and typically less than 1% of the NTE threshold. This research was part of a comprehensive program to determine the “allowance” when PEMS are used for in-use compliance testing of heavy-duty diesel vehicles (HDDVs).     

On-road emission characteristics of heavy-duty diesel vehicles in Shanghai

On-road vehicle tests of nine heavy-duty diesel trucks were conducted using SEMTECH-D, an emissions measuring instrument provided by Sensors, Inc. The total length of roads for the tests was 186 km. Data were obtained for 37,255 effective driving cycles, including 17,216 on arterial roads, 15,444 on residential roads, and 4595 on highways. The impacts of speed and acceleration on fuel consumption and emissions were analyzed. Results show that trucks spend an average of 16.5% of the time in idling mode, 25.5% in acceleration mode, 27.9% in deceleration mode, and only 30.0% at cruise speed. The average emission factors of CO, total hydrocarbons (THC), and NO_x for the selected vehicles are (4.96±2.90), (1.88±1.03) and (6.54±1.90) g km⁻¹, respectively. The vehicle emission rates vary significantly with factors like speed and acceleration. The test results reflect the actual traffic situation and the current emission status of diesel trucks in Shanghai. The measurements show that low-speed conditions with frequent acceleration and deceleration, particularly in congestion conditions, are the main factors that aggravate vehicle emissions and cause high emissions of CO and THC. Alleviating congestion would significantly improve vehicle fuel economy and reduce CO and THC emissions.     

Validation of DNDC for 22 long-term N2O field emission measurements

Twenty-two long-term measurements of direct N₂O emissions from soils in an intensive agricultural area were used for the validation of the process-based DNDC model (version 8.3P). Model simulations were evaluated for temporal patterns of N₂O, NH₄⁺, NO₃⁻ and water-filled pore space (WFPS) and total N₂O emissions. Several soil and crop input parameter adjustments to the model were evaluated but only the recalculation of the WFPS at wilting point and at field capacity, using pedotransfer functions, resulted in a clear improvement of the simulated variables (WFPS in all cases, N₂O in some cases). Therefore, only this adjustment was made to DNDC 8.3P. This change, however, resulted for some cases (both cropland and grassland) in retardation of nitrate leaching and to a lesser extent of NH₄⁺ to the deeper soil layers. The goodness of fit of the simulated temporal pattern of N₂O varied considerably between sites. The total simulated N₂O emissions from cropland showed a good agreement with the measurements, although there was a systematic overestimation of 7.4 kg N₂O-N ha⁻¹. Grassland soils, in contrast, gave a low agreement between total simulated and measured N₂O losses. On the basis of all measured data a regional emission factor of 3.16 with a 95% confidence interval of −0.89 to 7.21 could be calculated. DNDC simulations resulted in an emission factor of 6.49 with a 95% confidence interval of 4.04–8.93. The overall outcome of the N₂O emission measurements and DNDC simulations were compared with several empirical regression models, which may be applicable for a temperate climate system. All of the tested regression models showed reliable results up to a N₂O emission of 10 kg N₂O-N ha⁻¹. Higher emissions, however, were systematically underestimated. Though DNDC both under- and overestimated specific sites, the general agreement, over the whole range between measurements and simulations of total N₂O losses (simulations=0.82×meas.+6.2), was better than for the different regression models.     

Field Method Comparison between Passive Air Samplers and Continuous Monitors for VOCs and NO2 in El Paso,Texas

Abstract

This study evaluates the performance of Model 3300 Ogawa Passive Nitrogen Dioxide (NO₂) Samplers and 3M 3520 Organic Vapor Monitors (OVMs) by comparing integrated passive sampling concentrations to averaged hourly NO₂ and volatile organic compound (VOC) measurements at two sites in El Paso, TX. Sampling periods were three time intervals (3-day weekend, 4-day weekday, and 7-day weekly) for three consecutive weeks. OVM concentrations were corrected for ambient pressure to account for higher elevation. Precise results (<5% relative standard deviation, RSD) were found for NO₂ measurements from collocated Ogawa samplers. Reproducibility was lower from duplicate OVMs for BTEX (benzene, toluene, ethylbenzene, and xylene isomers) VOCs (≥7% RSD for 2-day samples) with better precision for longer sampling periods. Comparison of Ogawa NO₂ samplers with chemiluminescence measurements averaged over the same time period suggested potential calibration problems with the chemiluminescence analyzer. For BTEX species, generally good agreement was obtained between OVMs and automated-gas chromatograph (auto-GC) measurements. The OVMs successfully tracked increasing levels of VOCs recorded by the auto-GCs.     

Responses of herbaceous plants to urban air pollution: Effects on growth, phenology and leaf surface characteristics

Vehicle exhaust emissions are a dominant feature of urban environments and are widely believed to have detrimental effects on plants. The effects of diesel exhaust emissions on 12 herbaceous species were studied with respect to growth, flower development, leaf senescence and leaf surface wax characteristics. A diesel generator was used to produce concentrations of nitrogen oxides (NO_x) representative of urban conditions, in solardome chambers. Annual mean NO_x concentrations ranged from 77 nl l^−l to 98 nl l⁻¹, with NO:NO₂ ratios of 1.4-2.2, providing a good experimental simulation of polluted roadside environments. Pollutant exposure resulted in species-specific changes in growth and phenology, with a consistent trend for accelerated senescence and delayed flowering. Leaf surface characteristics were also affected; contact angle measurements indicated changes in surface wax structure following pollutant exposure. The study demonstrated clearly the potential for realistic levels of vehicle exhaust pollution to have direct adverse effects on urban vegetation.     

Current and future emission estimates of exhaust gases and particles from shipping at the largest port in Korea

The emissions of exhaust gases (NO _x , SO₂, VOCs, and CO₂) and particles (e.g., PM) from ships traversing Busan Port in Korea were estimated over three different years (the years 2006, 2008, and 2009). This analysis was performed according to the ship operational modes (“at sea,” “maneuvering,” and “in port”) and ship types based on an activity-based method. The ship emissions for current (base year 2009) and future scenarios (years 2020 and 2050) were also compared. The annual emissions of SO₂, VOCs, PM, and CO₂ were highest (9.6?×?10³, 374, 1.2?×?10³, and 5.6?×?10⁵ ton year^?1, respectively) in 2008. In contrast, the annual NO _x emissions were highest (11.7?×?10³ ton year^?1) in 2006 due mainly to the high NO _x emission factor. The emissions of air pollutants for each ship operational mode differed considerably, with the largest emission observed in “in port” mode. In addition, the largest fraction (approximately 45–67 %) of the emissions of all air pollutants during the study period was emitted from container ships. The future ship emissions of most pollutants (except for SO₂ and PM) in 2020 and 2050 are estimated to be 1.4–1.8 and 4.7–6.1 times higher than those in 2009 (base year), respectively.     

Quantification of Variability and Uncertainty in Lawn and Garden Equipment NOx and Total Hydrocarbon Emission Factors

Abstract

Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NO_x emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NO_x. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (Els).     

Comparison of the effect of biodiesel-diesel and ethanol-diesel on the gaseous emission of a direct-injection diesel engine

Experiments were conducted on a 4-cylinder direct-injection diesel engine using ultralow sulfur diesel blended with biodiesel and ethanol to investigate the gaseous emissions of the engine under five engine loads at the maximum torque engine speed of 1800 rev min^?1. Four biodiesel blended fuels and four ethanol blended fuels with oxygen concentrations of 2%, 4%, 6% and 8% were used. With the increase of oxygen content in the blended fuels, the brake thermal efficiency improves slightly.For the diesel-biodiesel fuels, the brake specific HC and CO emissions decrease while the brake specific NO_x and NO₂ emissions increase. The emissions of formaldehyde, 1,3-butadiene, toluene, xylene and overall BTX (benzene, toluene, xylene) in general decrease, however, acetaldehyde and benzene emissions increase. For the diesel-ethanol fuels, the brake specific HC and CO emissions increase significantly at low engine load, NO_x emission decreases at low engine load but increases at high engine load. The emissions of benzene and BTX vary with engine load and ethanol content. Similar to the biodiesel-diesel fuels, the formaldehyde, 1,3-butadiene, toluene and xylene emissions decrease while the acetaldehyde and NO₂ emissions increase. Despite having the same oxygen contents in the blended fuels, there are significant differences in the gaseous emissions between the biodiesel-diesel blends and the ethanol-diesel blends.